From the course: TensorFlow: Neural Networks and Working with Tables
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Loss - TensorFlow Tutorial
From the course: TensorFlow: Neural Networks and Working with Tables
Loss
- [Instructor] The model that we've created, isn't smart. It doesn't know what sport shoes are or trainers or ankle boots, and it can't tell the difference between them. So we take an image of an ankle boot as our input. It passes through our model and we get a prediction. Now what makes neural networks special is that we can train it so that whenever you provide an ankle boot as an input, it learns this. The way we do this is to train it with loads of examples of ankle boot images, so that it gets good at this. And you can see that there are a couple of features with an ankle boot, for example, the high heel. So there's got to be some way when, whenever we pass an image of ankle boots, it predicts ankle boots as the output. And when we pass it an image of a sport shoe, it predicts these sports shoe and not ankle boots or a bag or a dress as the output. This is known as the loss function. So a loss function takes as input…
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